Analysing the trend of Islamophobia in Blog Communities using Machine Learning and Trend Analysis

Authors

Tiffany Massey, Ernst & Young Global LimitedFollow
Chintan Amrit, University of AmstedamFollow
Guido van Capelleveen, University of TwenteFollow

Abstract

Blogs have been instrumental in shaping public opinion, and constitute an important component of the burgeoning Social Media space. However, researchers have not considered the impact of blog posts and the comments on blog posts to understand public opinion on different topics. This article analyses the trend of Islamophobia in certain blog communities in UK, using public opinion from blog comments taken from a range of political blogs. A proportion of the blog comments were labelled manually, before being used to train an algorithm to label the remaining comments. The algorithms gave varying results, the best being a Bagging algorithm – which is an ensemble algorithm that combines multiple algorithms. After labelling these comments, we answered our research question: Can one identify the trend in Islamophobia by analysing blog comments and if it is related to terror attacks in a particular country? We concluded that there has not been a rise in Islamophobia, but that terror attacks in the UK and abroad caused spikes in anti-Islam comments on the blogs. The main contribution of our research is in demonstrating a method for analysing blog comments to identify the trend in Islamophobia in the blog communities of a country.

Recommended Citation

Massey, Tiffany; Amrit, Chintan; and van Capelleveen, Guido, "Analysing the trend of Islamophobia in Blog Communities using Machine Learning and Trend Analysis" (2020). In Proceedings of the 28th European Conference on Information Systems (ECIS), An Online AIS Conference, June 15-17, 2020.
https://aisel.aisnet.org/ecis2020_rp/188